Computer vision has many applications, and is generally characterized by the use of a digital imaging system to produce an image, which is then analyzed with a computer for a subsequent decision. Many applications of computer vision involve identifying and locating objects in the image. Other applications of computer vision involve tracking a moving object. The camera or other image capturing device is the "observer" and the moving object is the "target".
To achieve computer vision in these applications, some methods use computations based on optical flow. In general terms, optical flow is understood by remembering that an image is a digitized representation of a continuous intensity variation of a scene in the physical world. The image changes as the objects in view, or the observer, or both, move with respect to each other. This movement gives rise to an optical flow, which associates a two dimensional velocity with each point on the two dimensional image plane. The result is an instantaneous velocity field on the image plane, which represents the optical flow of a number of points.
The optical flow reveals information about the shape of objects in the scene, which become determinate if the motion parameters are known. Other applications of optical flow include recovery of observer or target motion parameters.
A shortcoming of existing optical flow methods is the absence of methods for analyzing optical flow of a moving target that generates its own optical flow within an optical flow field due to a moving observer. Although one known method analyzes optical flow when the observer is moving, as well as the target, the observer's motion is only rotational and not translational. This method is described in an article by Ken-ichi Kanatani, entitled "Transformation of Optical Flow by Camera Rotation", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 10, No. 2, March 1988.
A need exists for a method of analyzing optical flow when both the observer and the target are moving with complete freedom of motion.